Muscle force is modulated by sequential recruitment and firing rates of motor units (MUs). However, discrepancies exist in the literature regarding the relationship between MU firing rates and their recruitment, presenting two contrasting firing-recruitment schemes. The first firing scheme, known as "onion skin," exhibits low-threshold MUs firing faster than high-threshold MUs, forming separate layers akin to an onion. This contradicts the other firing scheme, known as "reverse onion skin" or "afterhyperpolarization (AHP)," with low-threshold MUs firing slower than high-threshold MUs. To study this apparent dichotomy, we used a high-fidelity computational model that prioritizes physiological fidelity and heterogeneity, allowing versatility in the recruitment of different motoneuron types. Our simulations indicate that these two schemes are not mutually exclusive but rather coexist. The likelihood of observing each scheme depends on factors such as the motoneuron pool activation level, synaptic input activation rates, and MU type. The onion skin scheme does not universally govern the encoding rates of MUs but tends to emerge in unsaturated motoneurons (cells firing < their fusion frequency that generates peak force), whereas the AHP scheme prevails in saturated MUs (cells firing at their fusion frequency), which is highly probable for slow (S)-type MUs. When unsaturated, fast fatigable (FF)-type MUs always show the onion skin scheme, whereas S-type MUs do not show either one. Fast fatigue-resistant (FR)-type MUs are generally similar but show weaker onion skin behaviors than FF-type MUs. Our results offer an explanation for the longstanding dichotomy regarding MU firing patterns, shedding light on the factors influencing the firing-recruitment schemes.NEW & NOTEWORTHY The literature reports two contrasting schemes, namely the onion skin and the afterhyperpolarization (AHP) regarding the relationship between motor units (MUs) firing rates and recruitment order. Previous studies have examined these schemes phenomenologically, imposing one scheme on the firing-recruitment relationship. Here, we used a high-fidelity computational model that prioritizes biological fidelity and heterogeneity to investigate motoneuron firing schemes without bias toward either scheme. Our objective findings offer an explanation for the longstanding dichotomy on MU firing patterns.